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Leaf Recognition for Plant Classification Using GLCM and PCA Methods


Affiliations
1 Department of Computer Science, University of Mysore, Mysore - 570 006, India
 

In this paper, the image processing techniques has been used in order to classify the plants by applying on the leaves images. To extract the leaves texture features, the Gray-Level Co-occurrence matrix (GLCM) and Principal Component Analysis (PCA) algorithms have been considered. The Algorithms are trained by 390 leaves to classify 13 kinds of plants with 65 new or deformed leaves images. The result indicates that the accuracy for the GLCM method is 78% while the accuracy for the PCA method is 98%.

Keywords

Classification, GLCM, PCA, Feature Extraction.
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  • Leaf Recognition for Plant Classification Using GLCM and PCA Methods

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Authors

Abdolvahab Ehsanirad
Department of Computer Science, University of Mysore, Mysore - 570 006, India
Y. H. Sharath Kumar
Department of Computer Science, University of Mysore, Mysore - 570 006, India

Abstract


In this paper, the image processing techniques has been used in order to classify the plants by applying on the leaves images. To extract the leaves texture features, the Gray-Level Co-occurrence matrix (GLCM) and Principal Component Analysis (PCA) algorithms have been considered. The Algorithms are trained by 390 leaves to classify 13 kinds of plants with 65 new or deformed leaves images. The result indicates that the accuracy for the GLCM method is 78% while the accuracy for the PCA method is 98%.

Keywords


Classification, GLCM, PCA, Feature Extraction.